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People should look at this list and think a little differently about the freelance economy,” says Adam Ozimek, Upwork’s chief economist. “There’s too much focus on a narrow corner of the freelance economy and lower-skilled workers. This report shows how diverse this segment of the economy is and how much of it is high-skilled work.”Nearly 60 million Americans freelanced in 2019, either full-time or part-time, representing more than a third of the American workforce, according to a separate study by Upwork and Freelancers Union. Skilled services were the most common type of freelance work.A study by MBO Partners found that more than half of full-time independent workers say that they feel more financially secure in their current roles than in traditional jobs. That report found that there are more than 15 million full-time freelancers, with 1 in 5 earning more than $100,000 per year.In the absence of a severe recession, experts say that 2020 holds plenty of opportunity for those freelance workers with professional skills.“High-end professionals are going to have a great year next year, whether they’re freelance or not,” said Steve King, a partner at Emergent Research, a company in Lafayette, California, that studies the independent workforce. “The job market is just so tight, and those skills are really hard to find.”Here’s a look at the highest-paying freelance jobs that should be in great demand after COVID-19 is over in 2020, according to Upwork. The annual income is based on a 40-hour workweek, 50 weeks a year.Job Category: Corporate lawSample career: Intellectual property attorney; corporate legal counselHourly rate: $85Potential annual income: $170,000*Job category: Contract lawSample career: Contract drafter; litigator; general counselHourly rate: $75Annual rate: $150,000Job Category: Financial plannerSample career: Financial modeling expert; CPA; financial estate-planning attorneyHourly rate: $62.50Annual rate: $125,000Job category: Management consultingSample career: Business consultantHourly rate: $60Annual rate: $120,000Job category: ERP/CRM softwareSample career: Solution architect; consultant; developerHourly rate: $60Annual rate: $120,000Job Category: Network & system administrationSample career: Network architect; ITHourly rate: $60Annual rate: $120,000Job Category: Data visualizationSample career: Developer; programmer; data visualization analyst; survey and research design consultantHourly rate: $50Annual rate: $100,000Job Category: Machine learningSample career: Deep learning analytics consultant; predictive analytics consultantHourly rate: $50Annual rate: $100,000Job category: Quantitative analysisSample career: Professor of economics; statistical analystHourly rate: $50Annual rate: $100,000Job Category: PresentationsSample career: Presentation designer and writerHourly rate: $50Annual rate: $100,000Job category: Database administrationSample career: Data engineer; systems engineerHourly rate: $50Annual rate: $100,000Job category: Display advertisingSample career: Graphic designer; internet marketerHourly rate: $50Annual rate: $100,000Job category: E-mail and marketing automationSample career: Marketing expert; developer; senior marketing strategist; consultantHourly rate: $50Annual rate: $100,00Job category: Marketing strategySample career: Digital marketing consultant; copywriter; B2B marketing specialistHourly rate: $50Annual rate: $100,000Job category: SEM — Search engine marketingSample career: Google Adword ExpertHourly rate: $50Annual rate: $100,000Job category: Desktop software developmentSample career: Full-stack senior web developer; customer software developerHourly rate: $50Annual rate: $100,000Job category: e-commerce developmentSample career: Developer; online marketing and e-commerce solutions expert; e-commerce integration and automation consultingHourly rate: $50Annual rate: $100,000Job category: Mobile developmentSample career: iOS developer; Android Developer; mobile app developerHourly rate: $50Annual rate: $100,000Job category: Scripts & UtilitiesSample career: Google Sheets Experts; Apps Scripts expert; Excel automation specialistHourly rate: $49Annual rate: $98,000Job category: Physical designSample career: Industrial design engineer; product developer; global visual merchandising managerHourly rate: $45Annual rate: $90,000Job Category: Mechanical engineeringSample career: Mechanical engineer; structural engineer and designerHourly rate: $45Annual rate: $90,000Job Category: Product designSample career: User-experience consultant; product designerHourly rate: $45Annual rate: $90,000Job Category: Web and mobile designSample career: Web and mobile app development; user-experience designerHourly rate: $45Annual rate: $90,000Job Category: Web developmentSample career: Full-stack web development; business systems expert; user-experience designer; front-end developerHourly rate: $45Annual rate: $90,000Job category: Resumes & cover lettersSample career: Professional development writer; career coach; cover letter and LinkedIn supportHourly rate: $45Annual rate: $90,000I hope now your concept is clear :)

When most people think of the future of technology in medicine, they imagine robots performing surgery, smart scanners, or at least much more confident diagnoses. But we haven't seen this kind of innovation in most fields. One glaring example of this is in the field of pathology.The growth in number of requests for cancer screening will not be met by just hiring more pathologists. We need something better.What most people don’t realize is that even in this world of self driving cars and plans for travel to Mars, pathologists still run glass slides with tissue or fluid samples by courier from lab to lab for consultation, and rely heavily on manual slide viewing through an optical microscope lens. This leaves two very large opportunities for improvement: reduction of human errors made during manual slide viewing and finding the flexibility to do more, faster.Breast cancer identification and classification, as an example, requires very careful analysis of tissue samples to identify and quantify specific biomarkers. Doing this manually requires a slow and methodical scan over samples to find and quantify these indicators. This leaves a lot of room for error due to many human factors, such as fatigue and experience; and with the field of cancer research’s constant evolution, it can become more and more difficult as identification methods evolve.To combat this using the cloud and AI, pathologists can take gigapixel (1 billion or more pixels) stitched images of a tissue sample with file sizes reaching larger than that of a digital 4k movie on Blu-ray and upload them to the WebMicroscope Cloud Platform where our technology uses Artificial Intelligence (Deep Learning and Computer Vision to be more specific) to process the massive images to detect and quantify those cancer biomarkers. To put that into perspective, this is like taking a satellite image of European continent and identifying and counting every pink car. These gigantic images of tissue and cell samples require easily scalable storage and processing capacity. Moving forward, we'll be using the NVIDIA P100 Tesla GPU instances in Microsoft Azure for this, the fastest AI GPU option in the cloud.Using the artificial intelligence algorithms trained for the specific application, we can support pathologists and researchers to improve their decision making workflow. For instance, you can train a neural network to identify any visible feature on tissue samples by feeding it thousands upon thousands of carefully labeled tissue samples, making it amazingly accurate and reproducible. The image analysis algorithm is tireless, it performs always the same way.Now, a pathologist can process a slide by taking a the gigapixel high resolution image and passing it through our web application, and in just a few minutes have a resulting image that contains a clear heatmap or direct pointers highlighting what they were originally searching for. Think of being able to view that satellite image of Europe with clear arrows pointing at all those pink cars, along with the ability to zoom all the way in to see each individual car and to be able to have a clear count of all of them.Through manual viewing, this is nearly impossible on that scale; but using our Deep Learning algorithms, we can perform this task extremely fast.Being in the cloud also allows additional benefits in terms of education, scalability, and collaboration.In many medical universities, pathology classes are still dependent on conventional microscopes and students are huddled in small teams around microscopes taking turns at viewing tissue samples. With our WebMicroscope Cloud Platform students are already independently viewing the high resolution digital images on a their personal tablets, anywhere and anytime .In terms of scalability, with the growing volume of tissue samples and the shortage of the pathologist workforce, there is an immediate need to be able to scale sample assessment. This technology allows us to enable Pathologists and researchers to do their job faster, and more accurately than ever before.Because this is all in the cloud, getting a second opinion becomes extremely easy. Just sharing the image file within the platform with other users takes a few clicks. Drastically improved when compared to sending the physical glass slide sample to different labs.

To answer questions like this one accurately we don’t have to rely on creative and naive interpretations of folk tales and stories written down by authors centuries, no, millennia after the facts they are supposed to describe and later collected by a few early scholars and largely self-taught ethnographic and anthropological dilettanti of the 19th and early 20th century, many of whom exposed ideas that are now considered completely inaccurate, legendary, eccentric or even made up. No, we don’t need that anymore. We can obviously read those sources, but not take them at face value, without any scientific evidence to back those claims up, particularly when those are of mythical nature.We also don’t have to make absurd extrapolations, like inferring truths about the long-gone historical past from modern racist sayings created by Northern Europeans against Mediterranean peoples, or making conclusions about the entire and average population of Europe based on random similarities in monumental stone architecture of Neolithic peoples all over the world or on one certain (possibly mythic) king, son of "the king of the Africans" (yep, that's how precise ancient narratives often were), that was supposedly residing in Ireland by the time the Saxons were already living in Britain (well after the peak of the Western Roman Empire).. We’re way past that stage after more than one century of huge advances in history, archaeology, anthropology and genetics.ABOVE: Etruscans, whose civilization thrived centuries before the Roman Empire, are depicted in the beautiful tomb paintings above. They were Central Italian people, among the southernmost of Europe.Shall we go to the 21st century, where we belong, please?Okay. Not only are the skulls of ancient Europeans from the Bronze Age and Iron Age (therefore, before the Roman Empire), as they were analyzed by anthropologists, totally compatible with the variation of skull types found in Europe today, but also nowadays we have access to the DNA of thousands of European people from before, during and after the Roman Empire.As the artistic depictions of people in art from the time and the forensic reconstructions of skulls and remarkably well preserved “bog bodies” already suggested to scholars, too, it has been increasingly proven that Europe has basically seen very few genetic changes since at least 3,000 years ago, except for internal migration and mixing within Europe itself, involving people who were mostly already quite similar to each other.ABOVE: A comparison between the DNA makeup of 14 individuals linked to the Nuragic civilization from Sardinia (Bronze Age) and thousans of DNA samples of individuals from modern ethnic groups. Yes, the people closest to the ancient Nuragic people are still the 21st century Sardinians.ABOVE: Comparing the DNA makeup of 14 ancient individuals from Bronze Age and Iron Age Italy and Bulgaria to the aforementioned database of modern DNA samples, we find that they would nowadays fit generally within the Southern European cluster, some closer to modern-day Spaniards, some others close to Italians from various regiosn of the peninsula or nearby areas (Sardinia and Corsica).ABOVE: Measuring the genetic distance between 14 ancient DNA samples from Neolithic and Bronze Age Ireland and from Bronze Age and Iron Age England and the thousands of DNA samples of present-day individuals from all over the world. While Neolithic Irish people were, as already noted, very similar to modern Sardinians, just like most Neolithic farmers throughout Europe before 5,000 years ago, the Bronze Age and Iron Age people of Ireland and England were instead already very closely related to the people living in that broad area now, like the English, Irish, Welsh and Scottish, or alternatively to other Northern Europeans, like Danes, Dutch and Norwegians.I could go on forever with this. There have been dozens, hundreds of peer-reviewed genetic studies on ancient DNA that confirm what I wrote above, and there are thousands of other ancient DNA samples that I could compare to modern individuals’ DNA makeup.The result would be the same: generally, the best way to find people who are close to people who lived in some part of Europe 2,000 to 4,000 years ago is to look for present-day people living in the same area or within a radius of hundreds of kilometers around it.Analysis of those people’s genetic architecture for skin color shows no dramatic contrast compared to that found in modern Europeans: some derived alleles for skin depigmentation, eye depigmentation and hair depigmentation did increase very gradually in frequency (therefore, no sudden change happened, it was a piecemeal evolutionary process), particularly in Central and Northern areas of Europe. Northern Europeans some 4,000–5,000 years would have higher percentages of people with brown eyes, brown hair and slightly darker skin color (they’d probably look more like those “tanned” modern Welsh and Irish people than like modern Nordic people) . That’s about as much visible change as it happened in most places.ABOVE: Ötzi, the famous “Ice Man” remarkably well preserved in the Alps, had his DNA analyzed and found to be a typical Neolithic European farmer, genetically similar to modern Sardinians and, less closely, to other South Europeans.However, the Europeans as a whole already had the combination of most or even all the usual light skin-related alleles that make modern people at least as light-skinned as the range of skin colors that you can find in West Asians and Southern Europeans (say, people like the Turks and Iberians) at least since the Neolithic period (starting in Europe ~8,500–9,000 years ago), and, in Eastern Europe, even further ago, since at least the Mesolithic period (before 10,000 years ago).Most Neolithic Europeans living west of the Carpathians were surprisingly similar to modern Sardinians in genetic makeup, despite such a long time and distance separating, say, farmers from Neolithic England and dwellers of Sardinian mountains and high plateaus. They indeed had the gracile, Mediterranean-like skull traits that can still be seen in modern Sardinians and, less so, other Southern Europeans.Much of Europe and particularly Northern Europe, indeed, has had an incredibly high degree of genetic continuity at least since the Early Bronze Age (i.e. around 4,500–4,000 years ago), probably because the migrations that happened in the meantime came mostly from lands already inhabited by closely related populations (e.g. the Anglo-Saxon and Norse migration to Britain in the Early Medieval era, the Germanic expansion to Central-Southern Germany and Austria, etc.).ABOVE: “Ava”, a woman from the extension of the Bell Beaker Culture in Britain, as reconstructed by an artistic team. She was closely related to modern Northern Europeans.The Romans in particular seem to have left a small genetic impact in most places they conquered (in Europe or in other continents), because their empire wasn’t predicated on annihilation and resettlement (that could’ve happened on a sporadic and local basis), but on cooptation of local elites, acculturation of people and economic integration to the empire. They didn’t have strong ethnic ties, the Empire itself was ruled multiple times by people without Roman origin, like the emperors from Illyria, Hispania and Germania.They wanted to explore the natural resources and workforce, and they didn’t care who your ancestors were or what your local or regional identity was as long as you “Romanized” and accepted the higher authority of Romans. By the year 200 A.D., millions of people who called themselves “Romans” were actually descendants mainly of Gauls, Iberians, Aquitanians, Illyrians, Etruscans, Thracians, Greeks etc. Romans didn’t care, as long as they behaved like “true Romans” and worked on behalf of Roman dominance (or at least didn’t make anything to harm it).